Aligning Clattses in Parallel Texts

This paper describes a method for the automatic alignment of parallel texts at clause level. The method features statistical techniques coupled with shallow linguistic processing. It presupposes a parallel bilingual corpus and identifies alignments between the clauses of the source and target language sides of the corpus. Parallel texts are first statistically aligned at sentence level and then tagged with their part-of-speech categories. Regular grammars functioning on tags, recognize clauses on both sides of the parallel text. A probabilistic model is applied next, operating on the basis of word occurrence and co-occurrence probabilities and character lengths. Depending on sentence size, possible alignments arc fed into a dynamic progranuning framework or a simulated annealing system in order to find or approxim~te the best alignment. 1he method has been tested on a Small Eng~ lish-Greek corpus consisting of texts relevant to software systems and has produced promising results in terms of correctly identified clause alignments.